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Statistical Disclosure Control for Microdata - Methods and ~ This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data.
Statistical Disclosure Control for Microdata. Methods and ~ Statistical Disclosure Control for Microdata. Methods and Applications in R. May 2017; . Download full -text PDF Read full . Copy link Link copied. Citations (16) Abstract. This book on .
Statistical Disclosure Control for Microdata: Methods and ~ Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the dat a before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data.
Statistical Disclosure Control for Microdata / SpringerLink ~ Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the dat. a before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data.
(PDF) Statistical Disclosure Control Methods for Microdata ~ Microaggregation is a family of methods for statistical disclosure control (SDC) of microdata (records on individuals and/or companies), that is, for masking microdata so that they can be released .
Statistical Disclosure Control (sdcMicro) / IHSN ~ SDCMicro is free, R-based open-source package for the generation of protected microdata for researchers and public use. Data from statistical agencies and other institutions are mostly confidential. This package can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. In addition, various risk estimation methods are
Statistical disclosure control for microdata : methods and ~ Abstract. This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data.
StatisticalDisclosureControlforMicrodata Using the R ~ Statistical Disclosure Control, Microdata, Software Development, R. 1 Introduction Nowadays a number of different concepts exist to make confidential data accessible to researchers and users. A short outline of these concepts is given below in order to point out the need for data masking and the need for flexible software for data masking.
Statistical Disclosure Control Methods for Microdata ~ In this paper we formulate three basic tasks of statistical disclosure control for microdata, analyze existent methods for achieving optimal ratio between minimal disclosure risk and minimal information loss, and substantiate an availability of masking methods interconnected with microdata wavelet transform. Keywords: Statistical Disclosure .
Microdata files - Istat ~ MIcro.STAT files are developed for some surveys starting from the relative File for research purpose to which methods of statistical disclosure control have been applied to reduce the risk of identification of statistical unit. In some cases, the calculations performed on the file mIcro.STAT may lead to results in some extent differing from .
Statistical Disclosure Control for Tabular Data in R ~ Statistical Disclosure Control for Tabular Data in R Kazuhiro Minami and Yutaka Abe National Statistics Center, Japan The 5th International Conference -New Challenges for Statistical Software - The Use of R in Official Statistics – November 7, 2017
Special Issue "Statistical Disclosure Control for Microdata" ~ High-quality papers are solicited to address both theoretical and practical issues of methods in statistical disclosure control. Potential topics include, but are not limited to, re-identification risk measurement, anonymization of data, utility of anonymized data, and methods to create synthetic data.
Statistical Disclosure Control Methods for Anonymization ~ Data from statistical agencies and other institutions are mostly confidential. This package can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. In addition, various risk estimation methods are included. Note that the package includes a graphical user interface that allows to use various methods of this package.
Practical Applications in Statistical Disclosure Control ~ Abstract. The aim is to show how statistical disclosure methods can be applied to data using the R-packages sdcMicro and sdcTable.. The reader of this chapter should be advised how popular methods in microdata protection and tabular protection can be applied within these packages to real-world data.
Statistical Disclosure Control with R – Mind Project ~ The “Statistical Disclosure Control with R” training course has been designed for organisations, governmental departments, research institutes and private companies, who process, manage and analyse socio-economic microdata and want to safeguard the identity of individuals and sensitive information using modern statistical approaches. The course provides an in-depth knowledge on theory .
Microdata anonymization / IHSN ~ Statistical agencies and other data producers are increasingly publishing microdata obtained from sample surveys, censuses, and administrative data collection systems. The dissemination of microdata is made necessary by a high demand from the research community, a push for transparency, and sometimes by legal or contractual obligations. This must be done in such a way that the
Statistical Disclosure Control / Wiley Online Books ~ Statistical disclosure control is combined with other tools such as administrative, legal and IT in order to define a proper data dissemination strategy based on a risk management approach. The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of .
On the connections between statistical disclosure control ~ Download PDF Download. Share. Export. Advanced. Information Sciences. Volume 151, May 2003, Pages 153-170. On the connections between statistical disclosure control for microdata and some artificial intelligence tools. . Table 1, Table 2 illustrate the application of masking methods. We consider first, in Table 1, .
New in-house course: Statistical Disclosure Control with R ~ We are pleased to announce that we have now made a new in-house course “Statistical Disclosure Control with R” available to our clients as part of our In-House Training Services.The course is focused on providing governmental and non-governmental organisations, researchers, private companies and other bodies involved in processing and analysis of socio-economic microdata with an .
Handbook on Statistical Disclosure Control / CROS ~ The CROS Portal is a content management system based on Drupal and stands for "Portal on Collaboration in Research and Methodology for Official Statistics".The CROS Portal is dedicated to the collaboration between researchers and Official Statisticians in Europe and beyond.
Microdata - Statistical Disclosure Control - Wiley Online ~ The purpose of statistical disclosure control (SDC) for microdata is to prevent confidential information from being linked to specific respondents when releasing a microdata file. The chapter starts by viewing the whole process of production of microdata for the users according to the five stages approach to SDC.
Statistical Disclosure Control for Micro-Data Using the R ~ Confidentiality can be achieved by applying statistical disclosure control (SDC) methods to the data in order to decrease the disclosure risk of data. The R package sdcMicro serves as an easy-to-handle, object-oriented S4 class implementation of SDC methods to evaluate and anonymize confidential micro-data sets.
: Statistical Disclosure Control (9781119978152 ~ The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of statistical disclosure control. Numerous examples and guidelines are also featured to illustrate the topics covered. Statistical Disclosure Control:
Statistical disclosure control - Statistics Netherlands ~ Statistics Netherlands is required by law to protect the privacy of its respondents as well as it can. This process, called statistical disclosure control, can be carried out in various ways. This report describes methods available at Statistics Netherlands for statistical disclosure control of both microdata and quantitative tables. In addtion, the protection of frequency tables and analysis .
Statistics Surveys - Project Euclid ~ This paper presents a review of proposed methods of statistical disclosure control and techniques for assessing the privacy of such methods under different definitions of disclosure. . Disclosure limitation in longitudinal linked data. Confidentiality, Disclosure, and Data Access: Theory and Practical Applications for Statistical Agencies .